On- and off-line identification of linear state-space models
نویسندگان
چکیده
منابع مشابه
on the effect of linear & non-linear texts on students comprehension and recalling
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15 صفحه اولSystem Identification of Linear Parameter Varying State-space Models
This chapter examines the estimation of multivariable linear models for which the parameters vary in a time-varying manner that depends in an affine fashion on a known or otherwise measured signal. These locally linear models which depend on a measurable operating point are known as linear parameter varying (LPV) models. The contribution here relative to previous work on the topic is that in th...
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In an earlier paper (Moonen et al. 1989), an identification scheme has been presented, for computing state space models for multivariable linear time-invariant systems making use of (possibly noisy) input-output measurements only. This procedure is heavily based on the singular value decomposition (SVD), a numerical technique known to be very robust and accurate when dealing with noisy data. Ma...
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The problem of MIMO recursive identiication is considered and analyzed within the framework of subspace-based state space system identiication (4SID). With respect to previous contributions to this area, in this paper the use of recent signal processing algorithms for the recursive update of the SVD is proposed. To accommodate for arbitrary correlation of the disturbances, an instrumental varia...
متن کاملSystem identification of nonlinear state-space models
This paper is concerned with the parameter estimation of a general class of nonlinear dynamic systems in state-space form. More specifically, a Maximum Likelihood (ML) framework is employed and an Expectation Maximisation (EM) algorithm is derived to compute these ML estimates. The Expectation (E) step involves solving a nonlinear state estimation problem, where the smoothed estimates of the st...
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ژورنال
عنوان ژورنال: International Journal of Control
سال: 1989
ISSN: 0020-7179
DOI: 10.1080/00207178908961241